below marketmost similar roles pay hereabove market
This role pays less than
91%
of similar roles. Most pay
$128,166–$211,200
— the blue band above.
At the midpoint, this role pays about
$115k
versus about
$170k
for comparable roles.
Based on 240 similar postings.
Employer
About Pacific Life
Pacific Life is a life insurance company offering a wide range of life insurance, annuity, and investment products and services to individuals, businesses, and pension plans. Industry: Life Insurance & Annuities
Pacific Life currently has
46 open roles
on FindRole.
Listed pay typically runs
$152,010–$185,790
across 27 roles with salary data.
JOB TITLE: Analytics Engineer
The Analytics Engineer joins the Analytics Engineering team within the Advanced Analytics function to transform enterprise data into trusted, reusable analytics products. This role involves collaborating with stakeholders, data engineers, and data scientists to translate business needs into tested, documented, and scalable analytical models. Key responsibilities include developing modular SQL transformations, creating semantic models, and building automated tests to ensure data quality. The position requires hands-on experience with dbt, Snowflake, Snowflake Cortex, AWS, and Python. Candidates must utilize modern engineering practices including Git, Azure DevOps, and CI/CD workflows. Additionally, the role involves using AI-assisted tools like Claude Code and GitHub Copilot to develop agentic solutions. The work focuses on capturing business definitions and rules to support reporting, machine learning, and AI-powered business solutions.
Develop and maintain modular SQL transformations and analytical data models using dbt and Snowflake.
Translate business requirements into clear data definitions, business rules, metrics, and semantic models.
Build automated tests and maintain documentation to ensure data accuracy, reliability, and lineage.
Contribute to the development and evaluation of Snowflake Cortex solutions and AI agents.
Manage work through Git, Azure DevOps, and CI/CD workflows to deliver controlled production changes.
Apply AI-assisted tools like Claude Code and GitHub Copilot to development and workflow automation.
Provide hands-on guidance and knowledge transfer to help business partners adopt analytics products.
Troubleshoot analytical models to improve query performance and modernize manual processes.
What we're looking for
Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Mathematics, Engineering, or a related field, or equivalent practical experience.
Typically at least 2–5 years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical role.
Hands-on professional experience with dbt and Snowflake, including developing, testing, documenting, and maintaining analytical data models.
Strong SQL skills and practical understanding of relational and dimensional modeling, data transformation, business logic, and query optimization.
Experience with Git version control, branching, pull requests, code reviews, automated testing, and CI/CD workflows using Azure DevOps (ADO) or a comparable platform.
Working knowledge of Python for scripting, automation, or data-related development.
Familiarity with AWS and cloud-based data environments (professional AWS experience is preferred).
Experience with Snowflake Cortex, AI agents, or generative AI solutions is preferred.
SQL
DAX
Power BI
Microsoft Fabric
Tabular Editor
ALM Toolkit
DAX Studio
Dimensional Modeling
Star Schema
CI/CD
Git
VertiPaq
SSAS
Epic Cogito
Composite Models